Compared to [1]}, the proposed mixup is able to generate as many as artificial word samples with a small amount of task-related unlabeled data. Different from [2]}, [3]}, where the label of generated training samples is binary(e.g., correct or mispronounced), proposed mixup can generate continuous scores for augmented data.
